{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "73bd968b-d970-4a05-94ef-4e7abf990827",
   "metadata": {},
   "source": [
    "Chapter 05\n",
    "\n",
    "# 平面直线关系\n",
    "Book_3《数学要素》 | 鸢尾花书：从加减乘除到机器学习 (第二版)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b95adb80-42fc-462f-936d-17a9b0daff10",
   "metadata": {},
   "source": [
    "这段代码使用Matplotlib库绘制了几组直线图，展示了直线的正交、平行、水平和垂直关系，并对图形的装饰进行了一些统一的处理。代码的主要流程如下：\n",
    "\n",
    "1. **导入必要库和函数定义**：\n",
    "   首先导入了Matplotlib和Numpy库。定义了一个自定义函数$fig\\_decor$，用于标准化图形样式。$fig\\_decor$函数主要完成以下几项设置：\n",
    "   - 给$x$和$y$轴添加标签；\n",
    "   - 在$x=0$和$y=0$的位置分别添加一条水平线和一条垂直线，以构建直角坐标系；\n",
    "   - 将$x$和$y$轴的刻度设置为从$-8$到$8$，步长为$1$；\n",
    "   - 使$x$轴和$y$轴比例保持一致，即单位长度相同；\n",
    "   - 设置坐标范围（$[-8, 8]$）和隐藏边框以简化视觉效果；\n",
    "   - 添加了灰色虚线样式的网格线，便于观察坐标变化。\n",
    "\n",
    "2. **定义线性空间**：\n",
    "   使用$np.linspace(-8, 8)$生成了从$-8$到$8$的$x$和$y$数组，作为绘制直线的自变量范围。定义这些数组有助于在相同的坐标系中绘制多个直线方程。\n",
    "\n",
    "3. **绘制正交直线**：\n",
    "   创建第一个图形窗口，并绘制两条互相正交的直线：\n",
    "   - 第一条直线的方程为$y_1 = 0.5 \\cdot x + 2$，其斜率为$0.5$，截距为$2$；\n",
    "   - 第二条直线的方程为$y_2 = -2 \\cdot x - 1$，其斜率为$-2$，截距为$-1$。\n",
    "   \n",
    "   两条直线的斜率满足相乘为$-1$的条件，因此它们在几何上互相垂直。\n",
    "\n",
    "4. **绘制平行直线**：\n",
    "   创建第二个图形窗口，并绘制两条平行直线：\n",
    "   - 第一条直线的方程为$y_1 = 0.5 \\cdot x + 2$；\n",
    "   - 第二条直线的方程为$y_2 = 0.5 \\cdot x - 4$。\n",
    "   \n",
    "   这两条直线具有相同的斜率$0.5$，因此它们在坐标平面上互相平行。\n",
    "\n",
    "5. **绘制水平直线**：\n",
    "   创建第三个图形窗口，并绘制两条水平直线：\n",
    "   - 第一条直线为$y_1 = 2$，即$y$值恒定为$2$；\n",
    "   - 第二条直线为$y_2 = -4$，即$y$值恒定为$-4$。\n",
    "   \n",
    "   水平直线的方程为$y = c$，其中$c$为常数，这意味着$y$的值在$x$变化时保持不变，因此这些直线平行于$x$轴。\n",
    "\n",
    "6. **绘制垂直直线**：\n",
    "   创建第四个图形窗口，并绘制两条垂直直线：\n",
    "   - 第一条直线为$x_1 = 2$，即$x$值恒定为$2$；\n",
    "   - 第二条直线为$x_2 = -4$，即$x$值恒定为$-4$。\n",
    "   \n",
    "   垂直直线的方程为$x = c$，其中$c$为常数，这意味着$x$的值在$y$变化时保持不变，因此这些直线平行于$y$轴。\n",
    "\n",
    "每组直线图通过调用$fig\\_decor$函数进行了统一的美化，使得图形风格一致，并且清晰地展示了每组直线的关系。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5430e302-97e8-4dbe-8009-2299b116b211",
   "metadata": {},
   "source": [
    "## 导入所需的库"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3db6145d-d4ee-47b2-a917-dd8059271897",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np  # 导入numpy库，用于生成数值数组\n",
    "import matplotlib.pyplot as plt  # 导入matplotlib库，用于绘图"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57b15183-ad36-4f91-9a6f-4f80ec5f9804",
   "metadata": {},
   "source": [
    "## 自定义函数 - 图形装饰"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2185d4cc-655b-4fce-9ff7-5d32019a040d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def fig_decor(ax):  # 定义图形装饰函数fig_decor，对输入的坐标轴进行美化设置\n",
    "    ax.set_xlabel('x')  # 设置x轴标签\n",
    "    ax.set_ylabel('y')  # 设置y轴标签\n",
    "    \n",
    "    ax.hlines(y=0, xmin=-8, xmax=8, color='k')  # 在y=0处绘制从-8到8的水平线\n",
    "    ax.vlines(x=0, ymin=-8, ymax=8, color='k')  # 在x=0处绘制从-8到8的垂直线\n",
    "    \n",
    "    ax.set_xticks(np.arange(-8, 8 + 1, step=1))  # 设置x轴刻度，范围为-8到8，步长为1\n",
    "    ax.set_yticks(np.arange(-8, 8 + 1, step=1))  # 设置y轴刻度，范围为-8到8，步长为1\n",
    "    \n",
    "    ax.axis('scaled')  # 设置坐标轴比例，使x和y轴单位长度一致\n",
    "    ax.grid(linestyle='--', linewidth=0.25, color=[0.5,0.5,0.5])  # 添加网格线，样式为虚线，颜色为灰色\n",
    "    \n",
    "    ax.set_xbound(lower=-8, upper=8)  # 设置x轴范围，限制为-8到8\n",
    "    ax.set_ybound(lower=-8, upper=8)  # 设置y轴范围，限制为-8到8\n",
    "    ax.spines['top'].set_visible(False)  # 隐藏上边框\n",
    "    ax.spines['right'].set_visible(False)  # 隐藏右边框\n",
    "    ax.spines['bottom'].set_visible(False)  # 隐藏下边框\n",
    "    ax.spines['left'].set_visible(False)  # 隐藏左边框"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f5e5c5c2-08bb-4bcc-b15d-b1d608b70182",
   "metadata": {},
   "source": [
    "## 定义数组 - x和y的线性空间"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "138647e4-f7ae-4e1c-9a11-aad0a291cfb6",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_array = np.linspace(-8, 8)  # 生成从-8到8的x坐标数组\n",
    "y_array = np.linspace(-8, 8)  # 生成从-8到8的y坐标数组"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c82f3995-9118-429c-bcb0-c81ea0b3b381",
   "metadata": {},
   "source": [
    "## 正交线 - 交叉直线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4ee59044-84a9-4182-8e88-12aff68a7d68",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()  # 创建新的图形和坐标轴\n",
    "\n",
    "y1 = 0.5 * x_array + 2  # 定义直线y1的方程，斜率为0.5，截距为2\n",
    "y2 = -2 * x_array - 1  # 定义直线y2的方程，斜率为-2，截距为-1\n",
    "\n",
    "ax.plot(x_array, y1)  # 绘制直线y1\n",
    "ax.plot(x_array, y2)  # 绘制直线y2\n",
    "fig_decor(ax)  # 调用装饰函数美化图形"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "81567931-6e53-42e0-8ffd-d07e10a15b1c",
   "metadata": {},
   "source": [
    "## 平行线 - 平行直线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7a9d2798-9b93-4413-ac08-921b9aa154f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()  # 创建新的图形和坐标轴\n",
    "\n",
    "y1 = 0.5 * x_array + 2  # 定义平行直线y1，斜率为0.5，截距为2\n",
    "y2 = 0.5 * x_array - 4  # 定义平行直线y2，斜率为0.5，截距为-4\n",
    "\n",
    "ax.plot(x_array, y1)  # 绘制平行直线y1\n",
    "ax.plot(x_array, y2)  # 绘制平行直线y2\n",
    "fig_decor(ax)  # 调用装饰函数美化图形"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f20698e0-63e0-484d-8544-e8af32886393",
   "metadata": {},
   "source": [
    "## 水平线 - 水平直线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9a2ff2f5-5cd3-4c71-bd5e-541bb84e4cd9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()  # 创建新的图形和坐标轴\n",
    "\n",
    "y1 = 0 * x_array + 2  # 定义水平直线y1，y值为2\n",
    "y2 = 0 * x_array - 4  # 定义水平直线y2，y值为-4\n",
    "\n",
    "ax.plot(x_array, y1)  # 绘制水平直线y1\n",
    "ax.plot(x_array, y2)  # 绘制水平直线y2\n",
    "fig_decor(ax)  # 调用装饰函数美化图形"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c75f4878-bda7-4fcf-8fc0-85df9dd16670",
   "metadata": {},
   "source": [
    "## 垂直线 - 垂直直线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2b42d41c-abb8-43ac-889f-54681002cc73",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()  # 创建新的图形和坐标轴\n",
    "\n",
    "x1 = 0 * y_array + 2  # 定义垂直直线x1，x值为2\n",
    "x2 = 0 * y_array - 4  # 定义垂直直线x2，x值为-4\n",
    "\n",
    "ax.plot(x1, y_array)  # 绘制垂直直线x1\n",
    "ax.plot(x2, y_array)  # 绘制垂直直线x2\n",
    "fig_decor(ax)  # 调用装饰函数美化图形"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
